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Activity Number: 232
Type: Contributed
Date/Time: Monday, August 4, 2014 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract #311157 View Presentation
Title: WITHDRAWN: Asymmetric Linear Regression Models with Epsilon Skew Gamma Distribution
Author(s): Ebtisam Abdulah and Hassan Elsalloukh
Companies: and University of Arkansas at Little Rock
Keywords: Epsilon skew Gamma ; Asymmetric distributions ; Linear regression models ; Bimodal distributions.
Abstract:

We propose a linear regression model with Epsilon Skew Gamma (ES?) error term as a robust model for prediction with asymmetric innovations regression models. The ES? warrants providing the best fit line that minimize the sum squares of the error. It can deal with skewed, bimodal, and tailed behavior error distribution. We provide estimation for both regression and distribution parameters, using least squares and maximum likelihood methods for the simple and multiple linear regression models. We investigate some properties of the estimators obtained from the ES? linear regression model.


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